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Numerical analysis for statisticians
紀錄類型:
書目-電子資源 : 單行本
正題名/作者:
Numerical analysis for statisticians/ Kenneth Lange.
作者:
Lange, Kenneth.
出版者:
New York :Springer,�999.
面頁冊數:
1 online resource (xv, 356 pages).
標題:
Mathematical Computing. -
電子資源:
Click here for online access to this book (查閱全文) (EBSCO eBook)
ISBN:
0387227245 (electronic bk.)
ISBN:
9780387227245 (electronic bk.)
Numerical analysis for statisticians
Lange, Kenneth.
Numerical analysis for statisticians
[electronic resource] /Kenneth Lange. - New York :Springer,�999. - 1 online resource (xv, 356 pages). - Statistics and computing. - Statistics and computing..
Includes bibliographical references and index.
Cover -- Preface -- Table of Contents -- 1. Recurrence Relations -- 2. Power Series Expansions -- 3. Continued Fraction Expansions -- 4. Asymptotic Expansions -- 5. Solution of Nonlinear Equations -- 6. Vector and Matrix Norms -- 7. Linear Regression and Matrix Inversion -- 8. Eigenvalues and Eigenvectors -- 9. Splines -- 10. The EM Algorithm -- 11. Newton's Method and Scoring -- 12. Variations on the EM Theme -- 13. Convergence of Optimization Algorithms -- 14. Constrained Optimization -- 15. Concrete Hilbert Spaces -- 16. Quadrature Methods -- 17. The Fourier Transform -- 18. The Finite Fourier Transform -- 19. Wavelets -- 20. Generating Random Deviates -- 21. Independent Monte Carlo -- 22. Bootstrap Calculations -- 23. Finite-State Markov Chains -- 24. Markov Chain Monte Carlo.
This book presents topics in numerical analysis for statisticians. It would be suitable as a text for a graduate course in statistical computing. The focus is on principles of numerical analysis intended to equip students to craft their own software and to understand the advantages and disadvantages of different numerical methods.
ISBN: 0387227245 (electronic bk.)
Source: EBL219497eBook Libraryhttp://www.eblib.comSubjects--Topical Terms:
168965
Mathematical Computing.
Index Terms--Genre/Form:
172687
Electronic books.
LC Class. No.: QA297 / .L34 1999eb
Dewey Class. No.: 518
Numerical analysis for statisticians
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